Abstract Primary nephrotic syndrome (NS) is a rare disease of glomerular filtration barrier failure that causes massive urinary excretion of protein. Morbidity and mortality from NS is related both to the disease and the non- specific medications used to try to treat it. NS is currently classified and treated according to histologic appearance (e.g. focal segmental glomerulosclerosis [FSGS], minimal change disease[MCD]) or response to steroid therapy. This descriptive taxonomy is nonspecific and does not illuminate NS's underlying pathobiology. To achieve increasingly precise and effective care for NS patients, a better understanding of its underlying molecular mechanisms is necessary. Human genetics studies in NS have proven a promising strategy to permit patient classification by molecular subtype and identify targets that will spur biomarker and drug discovery. To discover novel, and identify known, genetic determinants of NS, their clinical correlates, and the mechanisms by which they confer their harm, we are generating and analyzing deep whole genome sequencing and RNA-seq derived transcriptomic data from affected patients in a North American, population-based cohort. Using gene expression from the kidneys of patients with NS, we aim to discover genetic variants associated with NS via expression quantitative trait loci (eQTL) studies. Using eQTLs as an intermediate molecular phenotype improves power to detect significant associations and will also directly illuminate biologic pathways that would not have been detected otherwise. We will also determine the prevalence of known monogenic forms NS in this cohort using robust bioinformatics filtering paired with functional testing. We will describe clinical correlates via integration with baseline and longitudinal phenotyping. Beyond the polygenic model, we are equally determined to discover the penetrance of the immunosuppressant resistant phenotype among patients with Mendelian NS. Our lab has thus far performed preliminary eQTL and Mendelian studies on enrollees in the Nephrotic Syndrome Study Network, with promising results. Here, we will expand these studies, beginning in Aim 1 by using new WGS and RNA-seq datasets to discover glomerular and tubulointerstitial eQTLs and identify those specific to these kidney tissues vs other tissues. In Aim 2, we will localize these eQTLs to specific cell lineages via integration with single cell RNA-Seq data, identify those overlapping kidney-derived regulatory regions, and discover their association with biologic processes and clinical phenotypes. We will functionally test top candidate eQTLs in drosophila and kidney organoid systems. In Aim 3, we will use WGS data to discover the prevalence of NS due to known Mendelian causes. We will study clinical correlates of Mendelian NS in US patients and identify factors associated with complete remission among those with Mendelian disease. Finally, we will use the drosophila and organoids models to functionally screen the putative pathogenic variants we discover. Altogether, we expect these discoveries to expand our knowledge of the spectrum of NS-associated genetic variation, the clinical implications for those harboring them, and the mechanisms underlying their pathogenicity.